grazing

Bijeenkomst: EGF2015
Auteur: Delagarde R., Delaby L., Peyraud J.L. and Faverdin P.
ISBN: 978-9090-289-61-8
Jaar van uitgifte: 2015
Producttype: Paper
Robust modelling of pasture herbage intake by grazing dairy cows under a wide range of grazing and supplementary feeding strategies allows the better combination of high rates of pasture utilization and nutrition management in dairy systems. The GrazeIn model has been developed from 10 years at INRA (France) from extensive literature review and large experimental databases, and then validated at European level. It allows prediction of the effects of animal characteristics, sward nutritive value, grazing management (grazing system, pasture allowance, pasture mass, daily access time) and supplementation (concentrates and/or forages), along with their interactions, on daily pasture dry matter intake by grazing dairy cows. Grazing management and sward structural characteristics are, however, often unknown on farm. For that reason, a simplified version of the model describing sward state and management through only pre-grazing and post-grazing sward heights has also been developed, allowing easier use of the model for advising or teaching. After a brief description of the two versions of the model, the relative effects of the main factors affecting pasture intake are compared on a per-cow and on a per-hectare basis.

Bijeenkomst: EGF2015
Auteur: Ipema A.H., Holshof G. and De Mol R.M.
ISBN: 978-9090-289-61-8
Jaar van uitgifte: 2015
Producttype: Paper
In the Autograssmilk project funded by the EU-FP7 programme an experiment was conducted with the objective to study the potential of using new technologies for the optimisation and integration of automatic milking with cow grazing. Data were collected during the 2014 grazing season from a 60-cow herd. The herd was kept in the barn during the night (16:00-6:00) where 8.4 kg dry matter (DM) per cow per day of conserved forage was fed. During the day (6:00-16:00) the herd had access to a strip of grass with approximately 8 kg DM per cow per day. Cows were free to return to the barn for visiting the milking robot. Automatic milking-system visits and milk yields were collected per cow. The average milk yield was 26.1 kg milk per cow per day. Feeding time was measured with a sensor attached to the neck of each cow. The cows spent an average of 346 minutes per day for feeding/grazing. For forage fed in the barn, cows spent an average of 6.7 minutes feeding time per kg of milk, while for grazing 8.8 minutes per kg of milk was spent. Older cows were significantly more efficient than heifers in their feeding time in the barn, whereas for grazing the differences were smaller.

Bijeenkomst: EGF2015
Auteur: Jiménez-Calderón J.D., Santiago C., Martínez-Fernández A. and Vicente F.
ISBN: 978-9090-289-61-8
Jaar van uitgifte: 2015
Producttype: Paper
Nowadays, a wide range of dairy farms coexist: from family farms to large-scale dairy farms. In order to determine the feeding systems of the dairy farms in Asturias (Spain), a sample of close to 2% of the total number of dairy farms (2,446) was randomly selected and surveyed. Farms were stratified according to their milk quota into four groups: 500 Mg year‑1. Milk yields in each group were 6,120, 7,525, 7,997 and 9,537 kg cow‑1 per lactation, respectively (P

Bijeenkomst: EGF2015
Auteur: Spörndly E., Andersson S., Pavard N., Le Goc S.
ISBN: 978-9090-289-61-8
Jaar van uitgifte: 2015
Producttype: Paper
In an automatic milking unit, a daytime grazing system with production pasture (group P) was compared with offering cows a small grass-covered paddock only for exercise and recreation, i.e. exercise pasture (group E). Two experiments (Exp1 and Exp2) were performed during 12 and 5 weeks with 53 cows and 42 cows, respectively. Group P was offered new pasture daily with night-time access to grass silage ad libitum (Exp1) or in restricted amounts (Exp2). Group E was offered exercise pasture and silage ad libitum during 24 (Exp1) or 16 hours (Exp2) daily. In Exp1, group P had significantly (P

Bijeenkomst: EGF2015
Auteur: Spörndly E. and Karlsson M.
ISBN: 978-9090-289-61-8
Jaar van uitgifte: 2015
Producttype: Paper
A field study on management during the pasture season was conducted on 20 Swedish farms with at least two automatic milking (AM) units and over 130 cows registered in the official control system. The objective was to compare milk production during indoor and pasture seasons, and to study cow traffic management during the pasture season. Using data from the official monthly control milkings, average yield of milked cows during winter (November-March) and summer ( June-August) seasons were analysed using a mixed model with farm as repeated subject and season as variable. Days in milk and cows per robot were tested in the model but were non-significant. Milk yield was 30.1 and 28.4 kg energy corrected milk in winter and summer season, respectively (P

Bijeenkomst: EGF2015
Auteur: Zom R.L.G., Holshof G., Ipema A.H. and De Mol R.M.
ISBN: 978-9090-289-61-8
Jaar van uitgifte: 2015
Producttype: Paper
An experiment was conducted with the objective of evaluating whether the combined data from grazing and rumen pH sensors could be used to support grazing management. Data were collected during the 2014 grazing season from a 60-cow herd. The average milk yield was 26.1 kg milk cow‑1 day‑1. The cows were housed during the night (16:00-06:00 h) and received 8.4 kg dry matter (DM) of conserved forage cow‑1 day‑1. During the daytime (06:00-16:00 h) the cows were strip-grazed. Daily, the cows were given an edible herbage allowance of approximately 8 kg DM above 5 cm stubble height cow‑1. Automatic milking system visits and milk yields were collected per cow. Concentrates were fed during milking with a transponder-controlled concentrate dispenser. Each cow was equipped with a grazing sensor to measure grazing time. Eight cows were equipped with boluses to measure rumen pH. Milk yield was recorded for each milking and milk composition was recorded weekly. Pre- and post-grazing sward height and herbage composition were recorded daily. Relationships between grass and sensor data and cow performance were derived on the basis of retrospective analysis of milk performance, grazing behaviour and rumen pH data. Rumen pH sensors appear to be of little value. There was no clear relationship between grazing activity and pasture characteristics.